Storage Strategies Guide

Creating storage strategies for Red Hat Ceph Storage clusters

This document provides instructions for creating storage strategies, including creating CRUSH hierarchies, estimating the number of placement groups, determining which type of storage pool to create, and managing pools.

Chapter 1. Overview

From the perspective of a Ceph client, interacting with the Ceph storage cluster is remarkably simple:

Connect to the Cluster

Create a Pool I/O Context

This remarkably simple interface is how a Ceph client selects one of the storage strategies you define. Storage strategies are invisible to the Ceph client in all but storage capacity and performance.

1.1. What are Storage Strategies?

A storage strategy is a method of storing data that serves a particular use case. For example, if you need to store volumes and images for a cloud platform like OpenStack, you might choose to store data on reasonably performant SAS drives with SSD-based journals. By contrast, if you need to store object data for an S3- or Swift-compliant gateway, you might choose to use something more economical, like SATA drives. Ceph can accommodate both scenarios in the same Ceph cluster, but you need a means of providing the SAS/SSD storage strategy to the cloud platform (e.g., Glance and Cinder in OpenStack), and a means of providing SATA storage for your object store.

Storage strategies include the storage media (hard drives, SSDs, etc.), the CRUSH maps that set up performance and failure domains for the storage media, the number of placement groups, and the pool interface. Ceph supports multiple storage strategies. Use cases, cost/benefit performance tradeoffs and data durability are the primary considerations that drive storage strategies.

Use Cases: Ceph provides massive storage capacity, and it supports numerous use cases. For example, the Ceph Block Device client is a leading storage backend for cloud platforms like OpenStack—​providing limitless storage for volumes and images with high performance features like copy-on-write cloning. By contrast, the Ceph Object Gateway client is a leading storage backend for cloud platforms that provides RESTful S3-compliant and Swift-compliant object storage for objects like audio, bitmap, video and other data.

Cost/Benefit of Performance: Faster is better. Bigger is better. High durability is better. However, there is a price for each superlative quality, and a corresponding cost/benefit trade off. Consider the following use cases from a performance perspective: SSDs can provide very fast storage for relatively small amounts of data and journaling. Storing a database or object index may benefit from a pool of very fast SSDs, but prove too expensive for other data. SAS drives with SSD journaling provide fast performance at an economical price for volumes and images. SATA drives without SSD journaling provide cheap storage with lower overall performance. When you create a CRUSH hierarchy of OSDs, you need to consider the use case and an acceptable cost/performance trade off.

Durability: In large scale clusters, hardware failure is an expectation, not an exception. However, data loss and service interruption remain unacceptable. For this reason, data durability is very important. Ceph addresses data durability with multiple deep copies of an object or with erasure coding and multiple coding chunks. Multiple copies or multiple coding chunks present an additional cost/benefit tradeoff: it’s cheaper to store fewer copies or coding chunks, but it may lead to the inability to service write requests in a degraded state. Generally, one object with two additional copies (i.e., size = 3) or two coding chunks may allow a cluster to service writes in a degraded state while the cluster recovers. The CRUSH algorithm aids this process by ensuring that Ceph stores additional copies or coding chunks in different locations within the cluster. This ensures that the failure of a single storage device or node doesn’t lead to a loss of all of the copies or coding chunks necessary to preclude data loss.

You can capture use cases, cost/benefit performance tradeoffs and data durability in a storage strategy and present it to a Ceph client as a storage pool.

Important

Ceph’s object copies or coding chunks make RAID obsolete. Do not use RAID, because Ceph already handles data durability, a degraded RAID has a negative impact on performance, and recovering data using RAID is substantially slower than using deep copies or erasure coding chunks.

1.2. Configuring Storage Strategies

Configuring storage strategies is about assigning Ceph OSDs to a CRUSH hierarchy, defining the number of placement groups for a pool, and creating a pool. The general steps are:

Define a Storage Strategy: Storage strategies require you to analyze your use case, cost/benefit performance tradeoffs and data durability. Then, you create OSDs suitable for that use case. For example, you can create SSD-backed OSDs for a high performance pool; SAS drive/SSD journal-backed OSDs for high-performance block device volumes and images; or, SATA-backed OSDs for low cost storage. Ideally, each OSD for a use case should have the same hardware configuration so that you have a consistent performance profile.

Define a CRUSH Hierarchy: Ceph rules select a node (usually the root) in a CRUSH hierarchy, and identify the appropriate OSDs for storing placement groups and the objects they contain. You must create a CRUSH hierarchy and a CRUSH rule for your storage strategy. CRUSH hierarchies get assigned directly to a pool by the CRUSH ruleset setting.

Calculate Placement Groups: Ceph shards a pool into placement groups. You need to set an appropriate number of placement groups for your pool, and remain within a healthy maximum number of placement groups in the event that you assign multiple pools to the same CRUSH ruleset.

Create a Pool: Finally, you must create a pool and determine whether it uses replicated or erasure-coded storage. You must set the number of placement groups for the pool, the ruleset for the pool and the durability (size or K+M coding chunks).

Remember, the pool is the Ceph client’s interface to the storage cluster, but the storage strategy is completely transparent to the Ceph client (except for capacity and performance).

Chapter 2. CRUSH Administration

The CRUSH (Controlled Replication Under Scalable Hashing) algorithm determines how to store and retrieve data by computing data storage locations.

Any sufficiently advanced technology is indistinguishable from magic.

-- Arthur C. Clarke

2.1. Introduction to CRUSH

The CRUSH map for your storage cluster describes your device locations within CRUSH hierarchies and a ruleset for each hierarchy that determines how Ceph stores data.

The CRUSH map contains at least one hierarchy of nodes and leaves. The nodes of a hierarchy, called "buckets" in Ceph, are any aggregation of storage locations (for example, rows, racks, chassis, hosts, and so on) as defined by their type. Each leaf of the hierarchy consists essentially of one of the storage devices in the list of storage devices. (note: storage devices or OSDs are added to the CRUSH map when you add an OSD to the cluster). A leaf is always contained in one node or "bucket." A CRUSH map also has a list of rules that determine how CRUSH stores and retrieves data.

The CRUSH algorithm distributes data objects among storage devices according to a per-device weight value, approximating a uniform probability distribution. CRUSH distributes objects and their replicas (or coding chunks) according to the hierarchical cluster map you define. Your CRUSH map represents the available storage devices and the logical buckets that contain them for the ruleset, and by extension each pool that uses the ruleset.

To map placement groups to OSDs across failure domains or performance domains, a CRUSH map defines a hierarchical list of bucket types (that is, under types in the generated CRUSH map). The purpose of creating a bucket hierarchy is to segregate the leaf nodes by their failure domains or performance domains or both. Failure domains include hosts, chassis, racks, power distribution units, pods, rows, rooms, and data centers. Performance domains include failure domains and OSDs of a particular configuration (for example, SSDs, SAS drives with SSD journals, SATA drives), and so on.

With the exception of the leaf nodes representing OSDs, the rest of the hierarchy is arbitrary, and you can define it according to your own needs if the default types do not suit your requirements. We recommend adapting your CRUSH map bucket types to your organization’s hardware naming conventions and using instance names that reflect the physical hardware names. Your naming practice can make it easier to administer the cluster and troubleshoot problems when an OSD or other hardware malfunctions and the administrator needs remote or physical access to the host or other hardware.

In the following example, the bucket hierarchy has four leaf buckets (osd 1-4), two node buckets (host 1-2) and one rack node (rack 1).

Since leaf nodes reflect storage devices declared under the devices list at the beginning of the CRUSH map, you do not need to declare them as bucket instances. The second lowest bucket type in your hierarchy usually aggregates the devices (that is, it’s usually the computer containing the storage media, and uses whatever term you prefer to describe it, such as "node", "computer", "server," "host", "machine", and so on). In high density environments, it is increasingly common to see multiple hosts/nodes per card and per chassis. You should account for card and chassis failure too, for example, the need to pull a card or chassis if a node fails can result in bringing down numerous hosts/nodes and their OSDs.

When declaring a bucket instance, you must specify its type, give it a unique name (string), assign it a unique ID expressed as a negative integer (optional), specify a weight relative to the total capacity/capability of its item(s), specify the bucket algorithm (usually straw), and the hash (usually 0, reflecting hash algorithm rjenkins1). A bucket can have one or more items. The items can consist of node buckets or leaves. Items can have a weight that reflects the relative weight of the item.

2.1.1. Dynamic Data Placement

Ceph Clients and Ceph OSDs both use the CRUSH map and the CRUSH algorithm.

Ceph Clients: By distributing CRUSH maps to Ceph clients, CRUSH empowers Ceph clients to communicate with OSDs directly. This means that Ceph clients avoid a centralized object look-up table that could act as a single point of failure, a performance bottleneck, a connection limitation at a centralized look-up server and a physical limit to the storage cluster’s scalability.

Ceph OSDs: By distributing CRUSH maps to Ceph OSDs, Ceph empowers OSDs to handle replication, backfilling and recovery. This means that the Ceph OSDs handle storage of object replicas (or coding chunks) on behalf of the Ceph client. It also means that Ceph OSDs know enough about the cluster to re-balance the cluster (backfilling) and recover from failures dynamically.

2.1.2. Failure Domains

Having multiple object replicas (or M coding chunks) helps preventing data loss, but it is not sufficient to address high availability. By reflecting the underlying physical organization of the Ceph Storage Cluster, CRUSH can model—and thereby address—potential sources of correlated device failures. By encoding the cluster’s topology into the cluster map, CRUSH placement policies can separate object replicas (or coding chunks) across different failure domains while still maintaining the desired pseudo-random distribution. For example, to address the possibility of concurrent failures, it may be desirable to ensure that data replicas (or coding chunks) are on devices using different shelves, racks, power supplies, controllers, and/or physical locations. This helps to prevent data loss and allows you to operate a cluster in a degraded state.

2.1.3. Performance Domains

Ceph can support multiple hierarchies to separate one type of hardware performance profile (for example, SSDs) from another type of hardware performance profile (for example, hard drives, hard drives with SSD journals, and so on). Performance domains—​hierarchies that take the performance profile of the underlying hardware into consideration—​are increasingly popular due to the need to support different performance characteristics. Operationally, these are just CRUSH maps with more than one root type bucket. Use case examples include:

VMs: Ceph hosts that serve as a back end to cloud platforms like OpenStack, CloudStack, ProxMox or OpenNebula tend to use the most stable and performant filesystem (that is, XFS) on SAS drives with a partitioned high performance SSD for journaling, because XFS does not journal and write simultaneously. To maintain a consistent performance profile, such use cases should aggregate similar hardware in a CRUSH hierarchy.

Object Storage: Ceph hosts that serve as an object storage back end for S3 and Swift interfaces may take advantage of less expensive storage media such as SATA drives that may not be suitable for VMs—​reducing the cost per gigabyte for object storage, while separating more economical storage hosts from more performant ones intended for storing volumes and images on cloud platforms. HTTP tends to be the bottleneck in object storage systems.

Cold Storage: Systems designed for cold storage (infrequently accessed data, or data retrieval with relaxed performance requirements) may take advantage of less expensive storage media and erasure coding. However, erasure coding may require a bit of additional RAM and CPU, and thus differ in RAM and CPU requirements from a host used for object storage or VMs.

SSD-backed Pools: SSDs are expensive, but they provide significant advantages over hard drives. SSDs have no seek time and they provide high total throughput. In addition to using SSDs for journaling, you can create SSD-backed pools in Ceph. Common use cases include high performance SSD pools (for example, mapping the .rgw.buckets.index pool for the Ceph Object Gateway to SSDs instead of SATA drives).

2.1.3.1. Use SSD Disks and SATA Disks Within the Same Machine

In order to use SSD disks and SATA disks on the same machine, you must create pools pointing to the SSD and SATA disks. The data going to these pools must be segregated by creating a new root hierarchy for the SSD drives. In the CRUSH map there needs to be a defined host for the SSD on each host and the SATA drives on each host. You can then create a rule for the SSD and set your pool to use this SSD ruleset.

To achieve this, you need to modify the CRUSH map (decompile the CRUSH map to modify—​see the Decompile a CRUSH Map section for further details). You must create two different root or entry points from which the CRUSH algorithm will go through to store objects. There will be one root for SSD disks and another one for SATA disks. The following example has two SATA disks and two SSD disks on each host, and three hosts in total. In a way, CRUSH thinks there are two different platforms.

To prevent the moved OSDs from moving back to their default CRUSH locations upon restart of the service, disable updating the CRUSH map on start of the daemon using osd crush update on start = false.

2.2. CRUSH Hierarchies

The CRUSH map is a directed acyclic graph, so it can accommodate multiple hierarchies (for example, performance domains). The easiest way to create and modify a CRUSH hierarchy is with the Ceph CLI; however, you can also decompile a CRUSH map, edit it, recompile it, and activate it.

When declaring a bucket instance with the Ceph CLI, you must specify its type and give it a unique name (string). Ceph automatically assigns a bucket ID, set the algorithm to straw, set the hash to 0 reflecting rjenkins1 and set a weight. When modifying a decompiled CRUSH map, assign the bucket a unique ID expressed as a negative integer (optional), specify a weight relative to the total capacity/capability of its item(s), specify the bucket algorithm (usually straw), and the hash (usually 0, reflecting hash algorithm rjenkins1).

A bucket can have one or more items. The items can consist of node buckets (for example, racks, rows, hosts) or leaves (for example, an OSD disk). Items can have a weight that reflects the relative weight of the item.

When modifying a decompiled CRUSH map, you can declare a node bucket with the following syntax:

In the foregoing example, note that the rack bucket does not contain any OSDs. Rather it contains lower level host buckets, and includes the sum total of their weight in the item entry.

2.2.1. CRUSH Location

A CRUSH location is the position of an OSD in terms of the CRUSH map’s hierarchy. When you express a CRUSH location on the command line interface, a CRUSH location specifier takes the form of a list of name/value pairs describing the OSD’s position. For example, if an OSD is in a particular row, rack, chassis and host, and is part of the default CRUSH tree, its crush location could be described as:

root=default row=a rack=a2 chassis=a2a host=a2a1

Note:

The order of the keys does not matter.

The key name (left of = ) must be a valid CRUSH type. By default these include root, datacenter, room, row, pod, pdu, rack, chassis and host. You may edit the CRUSH map to change the types to suit your needs.

You do not need to specify all the buckets/keys. For example, by default, Ceph automatically sets a ceph-osd daemon’s location to be root=default host={HOSTNAME} (based on the output from hostname -s).

2.2.1.1. Default ceph-crush-location Hook

Upon startup, Ceph gets the CRUSH location of each daemon using the ceph-crush-location tool by default. The ceph-crush-location utility returns the CRUSH location of a given daemon. Its CLI usage consists of:

By default, the ceph-crush-location utility returns a CRUSH location string for a given daemon. The location returned in order of precedence is based on:

A {TYPE}_crush_location option in the Ceph configuration file. For example, for OSD daemons, {TYPE} would be osd and the setting would look like osd_crush_location.

A crush_location option for a particular daemon in the Ceph configuration file.

A default of root=default host=HOSTNAME where the host name is returned by the hostname -s command.

In a typical deployment scenario, provisioning software (or the system administrator) can simply set the crush_location field in a host’s Ceph configuration file to describe that machine’s location within the datacenter or cluster. This provides location awareness to Ceph daemons and clients alike.

2.2.1.2. Custom Location Hooks

A custom location hook can be used in place of the generic hook for OSD daemon placement in the hierarchy. (On startup, each OSD ensures its position is correct.):

osd_crush_location_hook = /path/to/script

This hook is passed several arguments (below) and should output a single line to stdout with the CRUSH location description.:

where the --cluster name is typically 'ceph', the --id is the daemon identifier (the OSD number), and the daemon --type is typically osd.

2.2.2. Add a Bucket

To add a bucket instance to your CRUSH hierarchy, specify the bucket name and its type. Bucket names must be unique in the CRUSH map.

ceph osd crush add-bucket {name} {type}

If you plan to use multiple hierarchies (for example, for different hardware performance profiles), we recommend a colon-delimited naming convention of {type}:{name}. Where {type} is the type of hardware or use case and {name} is the bucket name.

For example, you could create a hierarchy for solid state drives (ssd), a hierarchy for SAS disks with SSD journals (hdd-journal), and another hierarchy for SATA drives (hdd):

If you have already used the Ansible automation application or another tool to add OSDs to your cluster, the host nodes can already be in the CRUSH map.

Once you have completed these steps, view your tree.

ceph osd tree

Notice that the hierarchy remains flat. You must move your buckets into hierarchical position after you add them to the CRUSH map.

2.2.3. Move a Bucket

When you create your initial cluster, Ceph has a default CRUSH map with a root bucket named default and your initial OSD hosts appear under the default bucket. When you add a bucket instance to your CRUSH map, it appears in the CRUSH hierarchy, but it does not necessarily appear under a particular bucket.

To move a bucket instance to a particular location in your CRUSH hierarchy, specify the bucket name and its type. For example:

You can also use ceph osd crush create-or-move to create a location while moving an OSD.

2.2.4. Remove a Bucket

To remove a bucket instance from your CRUSH hierarchy, specify the bucket name. For example:

ceph osd crush remove {bucket-name}

Or:

ceph osd crush rm {bucket-name}

Note

The bucket must be empty in order to remove it.

If you are removing higher level buckets (for example, a root like default), check to see if a pool uses a CRUSH rule that selects that bucket. If so, you need to modify your CRUSH rules; otherwise, peering fails.

2.2.5. Bucket Algorithms

When you create buckets using the Ceph CLI, Ceph sets the algorithm to straw by default. Ceph supports four bucket algorithms, each representing a tradeoff between performance and reorganization efficiency. If you are unsure of which bucket type to use, we recommend using a straw bucket. The bucket algorithms are:

Uniform: Uniform buckets aggregate devices with exactly the same weight. For example, when firms commission or decommission hardware, they typically do so with many machines that have exactly the same physical configuration (for example, bulk purchases). When storage devices have exactly the same weight, you can use the uniform bucket type, which allows CRUSH to map replicas into uniform buckets in constant time. With non-uniform weights, you should use another bucket algorithm.

List: List buckets aggregate their content as linked lists. Based on the RUSH (Replication Under Scalable Hashing) P algorithm, a list is a natural and intuitive choice for an expanding cluster: either an object is relocated to the newest device with some appropriate probability, or it remains on the older devices as before. The result is optimal data migration when items are added to the bucket. Items removed from the middle or tail of the list, however, can result in a significant amount of unnecessary movement, making list buckets most suitable for circumstances in which they never (or very rarely) shrink.

Tree: Tree buckets use a binary search tree. They are more efficient than list buckets when a bucket contains a larger set of items. Based on the RUSH (Replication Under Scalable Hashing) R algorithm, tree buckets reduce the placement time to O(log n), making them suitable for managing much larger sets of devices or nested buckets.

Straw (default): List and Tree buckets use a divide and conquer strategy in a way that either gives certain items precedence (for example, those at the beginning of a list) or obviates the need to consider entire subtrees of items at all. That improves the performance of the replica placement process, but can also introduce suboptimal reorganization behavior when the contents of a bucket change due an addition, removal, or re-weighting of an item. The straw bucket type allows all items to fairly “compete” against each other for replica placement through a process analogous to a draw of straws.

2.3. Ceph OSDs in CRUSH

Once you have a CRUSH hierarchy for the OSDs, add OSDs to the CRUSH hierarchy. You can also move or remove OSDs from an existing hierarchy. The Ceph CLI usage has the following values:

id

Description

The numeric ID of the OSD.

Type

Integer

Required

Yes

Example

0

name

Description

The full name of the OSD.

Type

String

Required

Yes

Example

osd.0

weight

Description

The CRUSH weight for the OSD.

Type

Double

Required

Yes

Example

2.0

root

Description

The name of the root bucket of the hierarchy or tree in which the OSD resides.

Type

Key-value pair.

Required

Yes

Example

root=default, root=replicated_ruleset, and so on

bucket-type

Description

One or more name-value pairs, where the name is the bucket type and the value is the bucket’s name. You can specify a CRUSH location for an OSD in the CRUSH hierarchy.

Type

Key-value pairs.

Required

No

Example

datacenter=dc1 room=room1 row=foo rack=bar host=foo-bar-1

2.3.1. Viewing OSDs in CRUSH

The ceph osd crush tree command prints CRUSH buckets and items in a tree view. Use this command to determine a list of OSDs in a particular bucket.

2.3.2. Adding an OSD to CRUSH

Adding an OSD to a CRUSH hierarchy is the final step before you start an OSD (rendering it up and in) and Ceph assigns placement groups to the OSD.

You must prepare an OSD before you add it to the CRUSH hierarchy. Deployment utilities, such the Ansible automation application, performs this step for you. See Adding/Removing OSDs for additional details.

The CRUSH hierarchy is notional, so the ceph osd crush add command allows you to add OSDs to the CRUSH hierarchy wherever you wish. The location you specify should reflect its actual location. If you specify at least one bucket, the command places the OSD into the most specific bucket you specify, and it moves that bucket underneath any other buckets you specify.

If you specify only the root bucket, the command attaches the OSD directly to the root. However, CRUSH rules expect OSDs to be inside of hosts or chassis, and host or chassis should be inside of other buckets reflecting your cluster topology.

You can also use ceph osd crush set or ceph osd crush create-or-move to add an OSD to the CRUSH hierarchy.

2.3.3. Moving an OSD within a CRUSH Hierarchy

If the deployment utility, such as the Ansible automation application added an OSD to the CRUSH map at a sub-optimal CRUSH location, or if your cluster topology changes, you can move an OSD in the CRUSH hierarchy to reflect its actual location.

Important

Moving an OSD in the CRUSH hierarchy means that Ceph will recompute which placement groups get assigned to the OSD, potentially resulting in significant redistribution of data.

You can also use ceph osd crush create-or-move to move an OSD within the CRUSH hierarchy.

2.3.4. Remove an OSD from a CRUSH Hierarchy

Removing an OSD from a CRUSH hierarchy is the first step when you want to remove an OSD from your cluster. When you remove the OSD from the CRUSH map, CRUSH recomputes which OSDs get the placement groups and data re-balances accordingly. See Adding/Removing OSDs for additional details.

To remove an OSD from the CRUSH map of a running cluster, execute the following:

ceph osd crush remove {name}

2.4. CRUSH Weights

The CRUSH algorithm assigns a weight value in terabytes (by convention) per OSD device with the objective of approximating a uniform probability distribution for write requests that assign new data objects to PGs and PGs to OSDs. For this reason, as a best practice, we recommend creating CRUSH hierarchies with devices of the same type and size, and assigning the same weight. We also recommend using devices with the same I/O and throughput characteristics so that you will also have uniform performance characteristics in your CRUSH hierarchy, even though performance characteristics do not affect data distribution.

Since using uniform hardware is not always practical, you may incorporate OSD devices of different sizes and use a relative weight so that Ceph will distribute more data to larger devices and less data to smaller devices.

2.4.1. Set an OSD’s Weight in Terabytes

To set an OSD CRUSH weight in Terabytes within the CRUSH map, execute the following command

ceph osd crush reweight {name} {weight}

Where:

name

Description

The full name of the OSD.

Type

String

Required

Yes

Example

osd.0

weight

Description

The CRUSH weight for the OSD. This should be the size of the OSD in Terabytes, where 1.0 is 1 Terabyte.

Type

Double

Required

Yes

Example

2.0

This setting is used when creating an OSD or adjusting the CRUSH weight immediately after adding the OSD. It usually does not change over the life of the OSD.

2.4.2. Set a Bucket’s OSD Weights

Using ceph osd crush reweight can be time-consuming. You can set (or reset) all Ceph OSD weights under a bucket (row, rack, node, and so on) by executing:

osd crush reweight-subtree <name>

Where,

name is the name of the CRUSH bucket.

2.4.3. Set an OSD’s in Weight

For the purposes of ceph osd in and ceph osd out, an OSD is either in the cluster or out of the cluster. That is how a monitor records an OSD’s status. However, even though an OSD is in the cluster, it may be experiencing a malfunction such that you do not want to rely on it as much until you fix it (for example, replace a storage drive, change out a controller, and so on).

You can increase or decrease the in weight of a particular OSD (that is, without changing its weight in Terabytes) by executing:

ceph osd reweight {id} {weight}

Where:

id is the OSD number.

weight is a range from 0.0-1.0, where 0 is not in the cluster (that is, it does not have any PGs assigned to it) and 1.0 is in the cluster (that is, the OSD receives the same number of PGs as other OSDs).

2.4.4. Set an OSD’s Weight by Utilization

CRUSH is designed to approximate a uniform probability distribution for write requests that assign new data objects PGs and PGs to OSDs. However, a cluster may become imbalanced anyway. This can happen for a number of reasons. For example:

Multiple Pools: You can assign multiple pools to a CRUSH hierarchy, but the pools may have different numbers of placement groups, size (number of replicas to store), and object size characteristics.

Custom Clients: Ceph clients such as block device, object gateway and filesystem shard data from their clients and stripe the data as objects across the cluster as uniform-sized smaller RADOS objects. So except for the foregoing scenario, CRUSH usually achieves its goal. However, there is another case where a cluster can become imbalanced: namely, using librados to store data without normalizing the size of objects. This scenario can lead to imbalanced clusters (for example, storing 100 1MB objects and 10 4MB objects will make a few OSDs have more data than the others).

Probability: A uniform distribution will result in some OSDs with more PGs and some with less. For clusters with a large number of OSDs, the statistical outliers will be further out.

threshold is a percentage of utilization such that OSDs facing higher data storage loads will receive a lower weight and thus fewer PGs assigned to them. The default value is 120, reflecting 120%. Any value from 100+ is a valid threshold. Optional.

weight_change_amount is the amount to change the weight. Valid values are greater than 0.0 - 1.0. The default value is 0.05. Optional.

number_of_OSDs is the maximum number of OSDs to reweight. For large clusters, limiting the number of OSDs to reweight prevents significant rebalancing. Optional.

no-increasing is off by default. Increasing the osd weight is allowed when using the reweight-by-utilization or test-reweight-by-utilization commands. If this option is used with these commands, it prevent the increasing the OSD weight, even if the OSD is underutilized. Optional.

Important

Executing reweight-by-utilization is recommended and somewhat inevitable for large clusters. Utilization rates may change over time, and as your cluster size or hardware changes, the weightings may need to be updated to reflect changing utilization. If you elect to reweight by utilization, you may need to re-run this command as utilization, hardware or cluster size change.

Executing this or other weight commands that assign a weight will override the weight assigned by this command (for example, osd reweight-by-utilization, osd crush weight, osd weight, in or out).

2.4.5. Set an OSD’s Weight by PG Distribution

In CRUSH hierarchies with a smaller number of OSDs, it’s possible for some OSDs to get more PGs than other OSDs, resulting in a higher load. You can reweight OSDs by PG distribution to address this situation by executing the following:

osd reweight-by-pg <poolname>

Where:

poolname is the name of the pool. Ceph will examine how the pool assigns PGs to OSDs and reweight the OSDs according to this pool’s PG distribution. Note that multiple pools could be assigned to the same CRUSH hierarchy. Reweighting OSDs according to one pool’s distribution could have unintended effects for other pools assigned to the same CRUSH hierarchy if they do not have the same size (number of replicas) and PGs.

2.4.6. Recalculate a CRUSH Tree’s Weights

CRUSH tree buckets should be the sum of their leaf weights. If you manually edit the CRUSH map weights, you should execute the following to ensure that the CRUSH bucket tree accurately reflects the sum of the leaf OSDs under the bucket.

osd crush reweight-all

2.5. Primary Affinity

When a Ceph Client reads or writes data, it always contacts the primary OSD in the acting set. For set [2, 3, 4], osd.2 is the primary. Sometimes an OSD is not well suited to act as a primary compared to other OSDs (for example, it has a slow disk or a slow controller). To prevent performance bottlenecks (especially on read operations) while maximizing utilization of your hardware, you can set a Ceph OSD’s primary affinity so that CRUSH is less likely to use the OSD as a primary in an acting set. :

ceph osd primary-affinity <osd-id> <weight>

Primary affinity is 1 by default (that is, an OSD may act as a primary). You may set the OSD primary range from 0-1, where 0 means that the OSD may NOT be used as a primary and 1 means that an OSD may be used as a primary. When the weight is < 1, it is less likely that CRUSH will select the Ceph OSD Daemon to act as a primary.

2.6. CRUSH Rules

CRUSH rules define how a Ceph client selects buckets and the primary OSD within them to store object, and how the primary OSD selects buckets and the secondary OSDs to store replicas or coding chunks. For example, you might create a rule that selects a pair of target OSDs backed by SSDs for two object replicas, and another rule that select three target OSDs backed by SAS drives in different data centers for three replicas.

A means of classifying a rule as belonging to a set of rules. Activated by setting the ruleset in a pool.

Purpose

A component of the rule mask.

Type

Integer

Required

Yes

Default

0

type

Description

Describes a rule for either a storage drive (replicated) or a RAID.

Purpose

A component of the rule mask.

Type

String

Required

Yes

Default

replicated

Valid Values

Currently only replicated

min_size

Description

If a pool makes fewer replicas than this number, CRUSH will not select this rule.

Type

Integer

Purpose

A component of the rule mask.

Required

Yes

Default

1

max_size

Description

If a pool makes more replicas than this number, CRUSH will not select this rule.

Type

Integer

Purpose

A component of the rule mask.

Required

Yes

Default

10

step take <bucket-name>

Description

Takes a bucket name, and begins iterating down the tree.

Purpose

A component of the rule.

Required

Yes

Example

step take data

step choose firstn <num> type <bucket-type>

Description

Selects the number of buckets of the given type. The number is usually the number of replicas in the pool (that is, pool size).

If <num> == 0, choose pool-num-replicas buckets (all available).

If <num> > 0 && < pool-num-replicas, choose that many buckets.

If <num> < 0, it means pool-num-replicas - {num}.

Purpose

A component of the rule.

Prerequisite

Follows step take or step choose.

Example

step choose firstn 1 type row

step chooseleaf firstn <num> type <bucket-type>

Description

Selects a set of buckets of {bucket-type} and chooses a leaf node from the subtree of each bucket in the set of buckets. The number of buckets in the set is usually the number of replicas in the pool (that is, pool size).

If <num> == 0, choose pool-num-replicas buckets (all available).

If <num> > 0 && < pool-num-replicas, choose that many buckets.

If <num> < 0, it means pool-num-replicas - <num>.

Purpose

A component of the rule. Usage removes the need to select a device using two steps.

Prerequisite

Follows step take or step choose.

Example

step chooseleaf firstn 0 type row

step emit

Description

Outputs the current value and empties the stack. Typically used at the end of a rule, but may also be used to pick from different trees in the same rule.

Purpose

A component of the rule.

Prerequisite

Follows step choose.

Example

step emit

Important

To activate one or more rules with a common ruleset number to a pool, set the ruleset number of the pool.

2.6.1. List Rules

To list CRUSH rules from the command line, execute the following:

ceph osd crush rule list
ceph osd crush rule ls

2.6.2. Dump a Rule

To dump the contents of a specific CRUSH rule, execute the following:

ceph osd crush rule dump {name}

2.6.3. Add a Simple Rule

To add a CRUSH rule, you must specify a rule name, the root node of the hierarchy you wish to use, the type of bucket you want to replicate across (for example, 'rack', 'row', and so on and the mode for choosing the bucket.

2.6.4. Add an Erasure Code Rule

To add a CRUSH rule for use with an erasure coded pool, you may specify a rule name and an erasure code profile.

ceph osd crush rule create-erasure {rulename} {profilename}

2.6.5. Remove a Rule

To remove a rule, execute the following and specify the CRUSH rule name:

ceph osd crush rule rm {name}

2.7. CRUSH Tunables

The Ceph project has grown exponentially with many changes and many new features. Beginning with the first commercially supported major release of Ceph, v0.48 (Argonaut), Ceph provides the ability to adjust certain parameters of the CRUSH algorithm, that is, the settings are not frozen in the source code.

A few important points to consider:

Adjusting CRUSH values may result in the shift of some PGs between storage nodes. If the Ceph cluster is already storing a lot of data, be prepared for some fraction of the data to move.

The ceph-osd and ceph-mon daemons will start requiring the feature bits of new connections as soon as they receive an updated map. However, already-connected clients are effectively grandfathered in, and will misbehave if they do not support the new feature. Make sure when you upgrade your Ceph Storage Cluster daemons that you also update your Ceph clients.

If the CRUSH tunables are set to non-legacy values and then later changed back to the legacy values, ceph-osd daemons will not be required to support the feature. However, the OSD peering process requires examining and understanding old maps. Therefore, you should not run old versions of the ceph-osd daemon if the cluster has previously used non-legacy CRUSH values, even if the latest version of the map has been switched back to using the legacy defaults.

2.7.1. The Evolution of CRUSH Tunables

Ceph clients and daemons prior to version 0.48 do not detect for tunables and are not compatible with version 0.48 and beyond, you must upgrade. The ability to adjust tunable CRUSH values has also evolved with major Ceph releases.

In Hierarchies with a small number of devices in the leaf buckets, some PGs map to fewer than the desired number of replicas. This commonly happens for hierarchies with "host" nodes with a small number (1-3) of OSDs nested beneath each one.

For large clusters, some small percentages of PGs map to less than the desired number of OSDs. This is more prevalent when there are several layers of the hierarchy. For example, row, rack, host, osd.

When some OSDs are marked out, the data tends to get redistributed to nearby OSDs instead of across the entire hierarchy.

Important

Red Hat strongly encourage upgrading both Ceph clients and Ceph daemons to major supported releases to take advantage of CRUSH tunables. Red Hat recommends that all cluster daemons and clients use the same release version.

Argonaut (Legacy)

This is the first commercially supported release of Ceph.

Version Requirements:

Ceph 0.48, 0.49 and later

Linux kernel 3.6 or later, including the RBD kernel clients

Supported CRUSH Tunables:

choose_local_tries: Number of local retries. Legacy value is 2, optimal value is 0.

choose_local_fallback_tries: Legacy value is 5, optimal value is 0.

choose_total_tries: Total number of attempts to choose an item. Legacy value was 19, subsequent testing indicates that a value of 50 is more appropriate for typical clusters. For extremely large clusters, a larger value might be necessary.

Bobtail

Version Requirements:

Ceph 0.55, 0.56.x and later

Linux kernel 3.9 or later, including the RBD kernel clients

Supported CRUSH Tunable:

chooseleaf_descend_once: Whether a recursive chooseleaf attempt will retry, or only try once and allow the original placement to retry. Legacy default is 0, optimal value is 1.

chooseleaf_vary_r: Whether a recursive chooseleaf attempt will start with a non-zero value of r, based on how many attempts the parent has already made. Legacy default is 0, but with this value CRUSH is sometimes unable to find a mapping. The optimal value, in terms of computational cost and correctness is 1. However, for legacy clusters that have lots of existing data, changing from 0 to 1 will cause a lot of data to move; a value of 4 or 5 will allow CRUSH to find a valid mapping but will make less data move.

straw_calc_version: There were some problems with the internal weights calculated and stored in the CRUSH map for straw buckets. Specifically, when there were items with a CRUSH weight of 0 or both a mix of weights and some duplicated weights CRUSH would distribute data incorrectly, that is, not in proportion to the weights. A value of 0 preserves the old, broken internal weight calculation; a value of 1 fixes the behavior. Setting the straw_calc_version to 1 and then adjusting a straw bucket, by either adding, removing, reweighting an item, or by using the reweight-all command, can trigger a small to moderate amount of data movement if the cluster has hit one of the problematic conditions. This tunable option is special because it has absolutely no impact concerning the required kernel version on the client side.

Hammer

The hammer tunable profile does not affect the mapping of existing CRUSH maps simply by changing the tunable profile, but a new bucket type, straw2 is now supported.

The new straw2 bucket type fixes several limitations in the original straw bucket. Specifically, the old straw buckets would change some mappings that should have changed when a weight was adjusted, while straw2 buckets achieves the original goal of only changing mappings to or from the bucket item whose weight has changed. The straw2 bucket is the default for any newly created buckets. Changing a bucket type from straw to straw2 will result in a reasonably small amount of data movement, depending on how much the bucket item weights vary from each other. When the weights are all the same no data will move, and when item weights vary significantly there will be more movement.

Jewel

Red Hat Ceph Storage 2 is supported on Red Hat Enterprise Linux 7.2 or above, but the jewel tunable profile is only supported on Red Hat Enterprise Linux 7.3 or above. The jewel tunable profile improves the overall behavior of CRUSH, such that it significantly reduces mapping changes when an OSD is marked out of the cluster.

chooseleaf_stable: Whether a recursive chooseleaf attempt will use a better value for an inner loop that greatly reduces the number of mapping changes when an OSD is marked out. The legacy value is 0, while the new value of 1 uses the new approach. Changing this value on an existing cluster will result in a very large amount of data movement as almost every PG mapping is likely to change.

Note

The CephFS kernel client is a technical preview feature in Red Hat Ceph Storage 2. For more details on the Ceph File System, see the Ceph File System Guide.

2.7.2. Tuning CRUSH

Before you tune CRUSH, you should ensure that all Ceph clients and all Ceph daemons use the same version. If you have recently upgraded, ensure that you have restarted daemons and reconnected clients.

The simplest way to adjust the CRUSH tunables is by changing to a known profile. Those are:

legacy: The legacy behavior from v0.47 (pre-Argonaut) and earlier.

argonaut: The legacy values supported by v0.48 (Argonaut) release.

bobtail: The values supported by the v0.56 (Bobtail) release.

firefly: The values supported by the v0.80 (Firefly) release.

hammer: The values supported by the v0.94 (Hammer) release.

jewel: The values supported by the v10.0.2 (Jewel) release.

optimal: The current best values.

default: The current default values for a new cluster.

You can select a profile on a running cluster with the command:

# ceph osd crush tunables <profile>

Note

This may result in some data movement.

Generally, you should set the CRUSH tunables after you upgrade, or if you receive a warning. Starting with version v0.74, Ceph will issue a health warning if the CRUSH tunables are not set to their optimal values, the optimal values are the default as of v0.73. To make this warning go away, you have two options:

Adjust the tunables on the existing cluster. Note that this will result in some data movement (possibly as much as 10%). This is the preferred route, but should be taken with care on a production cluster where the data movement may affect performance. You can enable optimal tunables with:

# ceph osd crush tunables optimal

If things go poorly (for example, too much load) and not very much progress has been made, or there is a client compatibility problem (old kernel cephfs or rbd clients, or pre-bobtail librados clients), you can switch back to an earlier profile:

# ceph osd crush tunables <profile>

For example, to restore the pre-v0.48 (Argonaut) values, execute:

# ceph osd crush tunables legacy

You can make the warning go away without making any changes to CRUSH by adding the following option to the [mon] section of the ceph.conf file:

mon warn on legacy crush tunables = false

For the change to take effect, restart the monitors, or apply the option to running monitors with:

# ceph tell mon.\* injectargs --no-mon-warn-on-legacy-crush-tunables

2.7.3. Tuning CRUSH, The Hard Way

If you can ensure that all clients are running recent code, you can adjust the tunables by extracting the CRUSH map, modifying the values, and reinjecting it into the cluster.

Extract the latest CRUSH map:

ceph osd getcrushmap -o /tmp/crush

Adjust tunables. These values appear to offer the best behavior for both large and small clusters we tested with. You will need to additionally specify the --enable-unsafe-tunables argument to crushtool for this to work. Please use this option with extreme care.:

Again, the special --enable-unsafe-tunables option is required. Further, as noted above, be careful running old versions of the ceph-osd daemon after reverting to legacy values as the feature bit is not perfectly enforced.

2.8. Editing a CRUSH Map

Generally, modifying your CRUSH map at runtime with the Ceph CLI is more convenient than editing the CRUSH map manually. However, there are times when you may choose to edit it, such as changing the default bucket types, or using a bucket algorithm other than straw.

2.8.4. Set a CRUSH Map

Ceph will input the compiled CRUSH map of the file name you specified as the CRUSH map for the cluster.

2.9. CRUSH Storage Strategy Examples

Suppose you want to have most pools default to OSDs backed by large hard drives, but have some pools mapped to OSDs backed by fast solid-state drives (SSDs). It’s possible to have multiple independent CRUSH hierarchies within the same CRUSH map to reflect different performance domains. Define two hierarchies with two different root nodes—​one for hard disks (for example, "root platter") and one for SSDs (for example, "root ssd") as shown below:

Your SSD pool can serve as the fast storage pool. Similarly, you could use the ssd-primary rule to cause each placement group in the pool to be placed with an SSD as the primary and platters as the replicas.

Chapter 3. Placement Groups (PGs)

Placement Groups (PGs) are invisible to Ceph clients, but they play an important role in Ceph Storage Clusters.

A Ceph Storage Cluster may require many thousands of OSDs to reach an exabyte level of storage capacity. Ceph clients store objects in pools, which are a logical subset of the overall cluster. The number of objects stored in a pool may easily run into the millions and beyond. A system with millions of objects or more cannot realistically track placement on a per-object basis and still perform well. Ceph assigns objects to placement groups, and placement groups to OSDs to make re-balancing dynamic and efficient.

All problems in computer science can be solved by another level of indirection, except of course for the problem of too many indirections.

-- David Wheeler

3.1. About Placement Groups

Tracking object placement on a per-object basis within a pool is computationally expensive at scale. To facilitate high performance at scale, Ceph subdivides a pool into placement groups, assigns each individual object to a placement group, and assigns the placement group to a primary OSD. If an OSD fails or the cluster re-balances, Ceph can move or replicate an entire placement group—​i.e., all of the objects in the placement groups—​without having to address each object individually. This allows a Ceph cluster to re-balance or recover efficiently.

When CRUSH assigns a placement group to an OSD, it calculates a series of OSDs—​the first being the primary. The osd_pool_default_size setting minus 1 for replicated pools, and the number of coding chunks M for erasure-coded pools determine the number of OSDs storing a placement group that can fail without losing data permanently. Primary OSDs use CRUSH to identify the secondary OSDs and copy the placement group’s contents to the secondary OSDs. For example, if CRUSH assigns an object to a placement group, and the placement group is assigned to OSD 5 as the primary OSD, if CRUSH calculates that OSD 1 and OSD 8 are secondary OSDs for the placement group, the primary OSD 5 will copy the data to OSDs 1 and 8. By copying data on behalf of clients, Ceph simplifies the client interface and reduces the client workload. The same process allows the Ceph cluster to recover and rebalance dynamically.

When the primary OSD fails and gets marked out of the cluster, CRUSH assigns the placement group to another OSD, which receives copies of objects in the placement group. Another OSD in the Up Set will assume the role of the primary OSD.

When you increase the number of object replicas or coding chunks, CRUSH will assign each placement group to additional OSDs as required.

Note

PGs do not own OSDs. CRUSH assigns many placement groups to each OSD pseudo-randomly to ensure that data gets distributed evenly across the cluster.

3.2. Placement Group Tradeoffs

Data durability and data distribution among all OSDs call for more placement groups but their number should be reduced to the minimum required for maximum performance to conserve CPU and memory resources.

3.2.1. Data Durability

Ceph strives to prevent the permanent loss of data. However, after an OSD fails, the risk of permanent data loss increases until the data it contained is fully recovered. Permanent data loss, though rare, is still possible. The following scenario describes how Ceph could permanently lose data in a single placement group with three copies of the data:

An OSD fails and all copies of the object it contains are lost. For all objects within a placement group stored on the OSD, the number of replicas suddenly drops from three to two.

Ceph starts recovery for each placement group stored on the failed OSD by choosing a new OSD to re-create the third copy of all objects for each placement group.

The second OSD containing a copy of the same placement group fails before the new OSD is fully populated with the third copy. Some objects will then only have one surviving copy.

Ceph picks yet another OSD and keeps copying objects to restore the desired number of copies.

The third OSD containing a copy of the same placement group fails before recovery is complete. If this OSD contained the only remaining copy of an object, the object is lost permanently.

Hardware failure isn’t an exception, but an expectation. To prevent the foregoing scenario, ideally the recovery process should be as fast as reasonably possible. The size of your cluster, your hardware configuration and the number of placement groups play an important role in total recovery time.

Small clusters don’t recover as quickly.

In a cluster containing 10 OSDs with 512 placement groups in a three replica pool, CRUSH will give each placement group three OSDs. Each OSD will end up hosting (512 * 3) / 10 = ~150 placement groups. When the first OSD fails, the cluster will start recovery for all 150 placement groups simultaneously.

It is likely that Ceph stored the remaining 150 placement groups randomly across the 9 remaining OSDs. Therefore, each remaining OSD is likely to send copies of objects to all other OSDs and also receive some new objects, because the remaining OSDs become responsible for some of the 150 placement groups now assigned to them.

The total recovery time depends upon the hardware supporting the pool. For example, in a 10 OSD cluster, if a host contains one OSD with a 1TB SSD, and a 10GB/s switch connects each of the 10 hosts, the recovery time will take M minutes. By contrast, if a host contains two SATA OSDs and a 1GB/s switch connects the five hosts, recovery will take substantially longer. Interestingly, in a cluster of this size, the number of placement groups has almost no influence on data durability. The placement group count could be 128 or 8192 and the recovery would not be slower or faster.

However, growing the same Ceph cluster to 20 OSDs instead of 10 OSDs is likely to speed up recovery and therefore improve data durability significantly. Why? Each OSD now participates in only 75 placement groups instead of 150. The 20 OSD cluster will still require all 19 remaining OSDs to perform the same amount of copy operations in order to recover. In the 10 OSD cluster, each OSDs had to copy approximately 100GB. In the 20 OSD cluster each OSD only has to copy 50GB each. If the network was the bottleneck, recovery will happen twice as fast. In other words, recovery time decreases as the number of OSDs increases.

In large clusters, PG count is important!

If the exemplary cluster grows to 40 OSDs, each OSD will only host 35 placement groups. If an OSD dies, recovery time will decrease unless another bottleneck precludes improvement. However, if this cluster grows to 200 OSDs, each OSD will only host approximately 7 placement groups. If an OSD dies, recovery will happen between at most of 21 (7 * 3) OSDs in these placement groups: recovery will take longer than when there were 40 OSDs, meaning the number of placement groups should be increased!

Important

No matter how short the recovery time, there is a chance for another OSD storing the placement group to fail while recovery is in progress.

In the 10 OSD cluster described above, if any OSD fails, then approximately 8 placement groups (i.e. 75 pgs / 9 osds being recovered) will only have one surviving copy. And if any of the 8 remaining OSDs fail, the last objects of one placement group are likely to be lost (i.e. 8 pgs / 8 osds with only one remaining copy being recovered). This is why starting with a somewhat larger cluster is preferred (e.g., 50 OSDs).

When the size of the cluster grows to 20 OSDs, the number of placement groups damaged by the loss of three OSDs drops. The second OSD lost will degrade approximately 2 (i.e. 35 pgs / 19 osds being recovered) instead of 8 and the third OSD lost will only lose data if it is one of the two OSDs containing the surviving copy. In other words, if the probability of losing one OSD is 0.0001% during the recovery time frame, it goes from 8 * 0.0001% in the cluster with 10 OSDs to 2 * 0.0001% in the cluster with 20 OSDs. Having 512 or 4096 placement groups is roughly equivalent in a cluster with less than 50 OSDs as far as data durability is concerned.

Tip

In a nutshell, more OSDs means faster recovery and a lower risk of cascading failures leading to the permanent loss of a placement group and its objects.

When you add an OSD to the cluster, it may take a long time top populate the new OSD with placement groups and objects. However there is no degradation of any object and adding the OSD has no impact on data durability.

3.2.2. Data Distribution

Ceph seeks to avoid hot spots—​i.e., some OSDs receive substantially more traffic than other OSDs. Ideally, CRUSH assigns objects to placement groups evenly so that when the placement groups get assigned to OSDs (also pseudo randomly), the primary OSDs store objects such that they are evenly distributed across the cluster and hot spots and network over-subscription problems cannot develop because of data distribution.

Since CRUSH computes the placement group for each object, but does not actually know how much data is stored in each OSD within this placement group, the ratio between the number of placement groups and the number of OSDs may influence the distribution of the data significantly.

For instance, if there was only one a placement group with ten OSDs in a three replica pool, Ceph would only use three OSDs to store data because CRUSH would have no other choice. When more placement groups are available, CRUSH is more likely to be evenly spread objects across OSDs. CRUSH also evenly assigns placement groups to OSDs.

As long as there are one or two orders of magnitude more placement groups than OSDs, the distribution should be even. For instance, 300 placement groups for 3 OSDs, 1000 placement groups for 10 OSDs etc.

The ratio between OSDs and placement groups usually solves the problem of uneven data distribution for Ceph clients that implement advanced features like object striping. For example, a 4TB block device might get sharded up into 4MB objects.

The ratio between OSDs and placement groups does not address uneven data distribution in other cases, because CRUSH does not take object size into account. Using the librados interface to store some relatively small objects and some very large objects can lead to uneven data distribution. For example, one million 4K objects totaling 4GB are evenly spread among 1000 placement groups on 10 OSDs. They will use 4GB / 10 = 400MB on each OSD. If one 400MB object is added to the pool, the three OSDs supporting the placement group in which the object has been placed will be filled with 400MB + 400MB = 800MB while the seven others will remain occupied with only 400MB.

3.2.3. Resource Usage

For each placement group, OSDs and Ceph monitors need memory, network and CPU at all times, and even more during recovery. Sharing this overhead by clustering objects within a placement group is one of the main reasons placement groups exist.

Minimizing the number of placement groups saves significant amounts of resources.

3.3. PG Count

The number of placement groups in a pool plays a significant role in how a cluster peers, distributes data and rebalances. Small clusters don’t see as many performance improvements compared to large clusters by increasing the number of placement groups. However, clusters that have many pools accessing the same OSDs may need to carefully consider PG count so that Ceph OSDs use resources efficiently.

Tip

Red Hat recommends 100 to 200 PGs per OSD.

3.3.1. PG Calculator

The PG calculator calculates the number of placement groups for you and addresses specific use cases. The PG calculator is especially helpful when using Ceph clients like the Ceph Object Gateway where there are many pools typically using same ruleset (CRUSH hierarchy). You may still calculate PGs manually using the guidelines in PG Count for Small Clusters and Calculating PG Count. However, the PG calculator is the preferred method of calculating PGs.

3.3.2. Configuring Default PG Counts

When you create a pool, you also create a number of placement groups for the pool. If you don’t specify the number of placement groups, Ceph will use the default value of 8, which is unacceptably low. You can increase the number of placement groups for a pool, but we recommend setting reasonable default values in your Ceph configuration file too.

osd pool default pg num = 100
osd pool default pgp num = 100

You need to set both the number of placement groups (total), and the number of placement groups used for objects (used in PG splitting). They should be equal.

3.3.3. PG Count for Small Clusters

Small clusters don’t benefit from large numbers of placement groups. So you should consider the following values:

Less than 5 OSDs set pg_num and pgp_num to 128.

Between 5 and 10 OSDs set pg_num and pgp_num to 512

Between 10 and 50 OSDs set pg_num and pgp_num to 1024

If you have more than 50 OSDs, you need to understand the tradeoffs and how to calculate the pg_num and pgp_num values. See Calculating PG Count.

As the number of OSDs increase, choosing the right value for pg_num and pgp_num becomes more important because it has a significant influence on the behavior of the cluster as well as the durability of the data when something goes wrong (i.e. the probability that a catastrophic event leads to data loss).

3.3.4. Calculating PG Count

If you have more than 50 OSDs, we recommend approximately 50-100 placement groups per OSD to balance out resource usage, data durability and distribution. If you have less than 50 OSDs, choosing among the PG Count for Small Clusters is ideal. For a single pool of objects, you can use the following formula to get a baseline:

(OSDs * 100)
Total PGs = ------------
pool size

Where pool size is either the number of replicas for replicated pools or the K+M sum for erasure coded pools (as returned by ceph osd erasure-code-profile get).

You should then check if the result makes sense with the way you designed your Ceph cluster to maximize data durability, data distribution and minimize resource usage.

The result should be rounded up to the nearest power of two. Rounding up is optional, but recommended for CRUSH to evenly balance the number of objects among placement groups.

For a cluster with 200 OSDs and a pool size of 3 replicas, you would estimate your number of PGs as follows:

(200 * 100)
----------- = 6667. Nearest power of 2: 8192
3

With 8192 placement groups distributed across 200 OSDs, that evaluates to approximately 41 placement groups per OSD. You also need to consider the number of pools you are likely to use in your cluster, since each pool will create placement groups too. Ensure that you have a reasonable maximum PG count.

3.3.5. Maximum PG Count

When using multiple data pools for storing objects, you need to ensure that you balance the number of placement groups per pool with the number of placement groups per OSD so that you arrive at a reasonable total number of placement groups. The aim is to achieve reasonably low variance per OSD without taxing system resources or making the peering process too slow.

In an exemplary Ceph Storage Cluster consisting of 10 pools, each pool with 512 placement groups on ten OSDs, there is a total of 5,120 placement groups spread over ten OSDs, or 512 placement groups per OSD. That may not use too many resources depending on your hardware configuration. By contrast, if you create 1,000 pools with 512 placement groups each, the OSDs will handle ~50,000 placement groups each and it would require significantly more resources. Operating with too many placement groups per OSD can significantly reduce performance, especially during rebalancing or recovery.

The Ceph Storage Cluster has a default maximum value of 300 placement groups per OSD. You can set a different maximum value in your Ceph configuration file.

mon pg warn max per osd

Tip

Ceph Object Gateways deploy with 10-15 pools, so you may consider using less than 100 PGs per OSD to arrive at a reasonable maximum number.

3.4. PG Command-Line Reference

The ceph CLI allows you to set and get the number of placement groups for a pool, view the PG map and retrieve PG statistics.

3.4.1. Set the Number of PGs

To set the number of placement groups in a pool, you must specify the number of placement groups at the time you create the pool. See Create a Pool for details. Once you set placement groups for a pool, you can increase the number of placement groups (but you cannot decrease the number of placement groups). To increase the number of placement groups, execute the following:

ceph osd pool set {pool-name} pg_num {pg_num}

Once you increase the number of placement groups, you must also increase the number of placement groups for placement (pgp_num) before your cluster will rebalance. The pgp_num should be equal to the pg_num. To increase the number of placement groups for placement, execute the following:

ceph osd pool set {pool-name} pgp_num {pgp_num}

3.4.2. Get the Number of PGs

To get the number of placement groups in a pool, execute the following:

ceph osd pool get {pool-name} pg_num

3.4.3. Get a Cluster PG Statistics

To get the statistics for the placement groups in your cluster, execute the following:

ceph pg dump [--format {format}]

Valid formats are plain (default) and json.

3.4.4. Get Statistics for Stuck PGs

To get the statistics for all placement groups stuck in a specified state, execute the following:

Inactive Placement groups cannot process reads or writes because they are waiting for an OSD with the most up-to-date data to come up and in.

Unclean Placement groups contain objects that are not replicated the desired number of times. They should be recovering.

Stale Placement groups are in an unknown state - the OSDs that host them have not reported to the monitor cluster in a while (configured by mon_osd_report_timeout).

Valid formats are plain (default) and json. The threshold defines the minimum number of seconds the placement group is stuck before including it in the returned statistics (default 300 seconds).

3.4.5. Get a PG Map

To get the placement group map for a particular placement group, execute the following:

ceph pg map {pg-id}

For example:

ceph pg map 1.6c

Ceph will return the placement group map, the placement group, and the OSD status:

osdmap e13 pg 1.6c (1.6c) -> up [1,0] acting [1,0]

3.4.6. Get a PGs Statistics

To retrieve statistics for a particular placement group, execute the following:

ceph pg {pg-id} query

3.4.7. Scrub a Placement Group

To scrub a placement group, execute the following:

ceph pg scrub {pg-id}

Ceph checks the primary and any replica nodes, generates a catalog of all objects in the placement group and compares them to ensure that no objects are missing or mismatched, and their contents are consistent. Assuming the replicas all match, a final semantic sweep ensures that all of the snapshot-related object metadata is consistent. Errors are reported via logs.

3.4.8. Revert Lost

If the cluster has lost one or more objects, and you have decided to abandon the search for the lost data, you must mark the unfound objects as lost.

If all possible locations have been queried and objects are still lost, you may have to give up on the lost objects. This is possible given unusual combinations of failures that allow the cluster to learn about writes that were performed before the writes themselves are recovered.

Currently the only supported option is "revert", which will either roll back to a previous version of the object or (if it was a new object) forget about it entirely. To mark the "unfound" objects as "lost", execute the following:

ceph pg {pg-id} mark_unfound_lost revert|delete

Important

Use this feature with caution, because it may confuse applications that expect the object(s) to exist.

Chapter 4. Pools

Ceph clients store data in pools. When you create pools, you are creating an I/O interface for clients to store data. From the perspective of a Ceph client (i.e., block device, gateway, etc.), interacting with the Ceph storage cluster is remarkably simple: create a cluster handle and connect to the cluster; then, create an I/O context for reading and writing objects and their extended attributes.

Create a Cluster Handle and Connect to the Cluster

To connect to the Ceph storage cluster, the Ceph client needs the cluster name (usually ceph by default) and an initial monitor address. Ceph clients usually retrieve these parameters using the default path for the Ceph configuration file and then read it from the file, but a user may also specify the parameters on the command line too. The Ceph client also provides a user name and secret key (authentication is on by default). Then, the client contacts the Ceph monitor cluster and retrieves a recent copy of the cluster map, including its monitors, OSDs and pools.

Create a Pool I/O Context

To read and write data, the Ceph client creates an i/o context to a specific pool in the Ceph storage cluster. If the specified user has permissions for the pool, the Ceph client can read from and write to the specified pool.

Ceph’s architecture enables the storage cluster to provide this remarkably simple interface to Ceph clients so that clients may select one of the sophisticated storage strategies you define simply by specifying a pool name and creating an I/O context. Storage strategies are invisible to the Ceph client in all but capacity and performance. Similarly, the complexities of Ceph clients (mapping objects into a block device representation, providing an S3/Swift RESTful service) are invisible to the Ceph storage cluster.

A pool provides you with:

Resilience: You can set how many OSD are allowed to fail without losing data. For replicated pools, it is the desired number of copies/replicas of an object. A typical configuration stores an object and one additional copy (i.e., size = 2), but you can determine the number of copies/replicas. For erasure coded pools, it is the number of coding chunks (i.e. m=2 in the erasure code profile)

Placement Groups: You can set the number of placement groups for the pool. A typical configuration uses approximately 50-100 placement groups per OSD to provide optimal balancing without using up too many computing resources. When setting up multiple pools, be careful to ensure you set a reasonable number of placement groups for both the pool and the cluster as a whole.

CRUSH Rules: When you store data in a pool, a CRUSH ruleset mapped to the pool enables CRUSH to identify a rule for the placement of each object and its replicas (or chunks for erasure coded pools) in your cluster. You can create a custom CRUSH rule for your pool.

Snapshots: When you create snapshots with ceph osd pool mksnap, you effectively take a snapshot of a particular pool.

Quotas: When you set quotas on a pool with ceph osd pool set-quota you may limit the maximum number of objects or the maximum number of bytes stored in the specified pool.

4.1. Pools and Storage Strategies

To manage pools, you can list, create, and remove pools. You can also view the utilization statistics for each pool.

The total number of placement groups for placement purposes. This value must be equal to the total number of placement groups, except for placement group splitting scenarios.

Type

Integer

Required

Yes. If not specified it is set to the value listed in the Ceph configuration file or to the default value.

Default

8

replicated or erasure

Description

The pool type which can be either replicated to recover from lost OSDs by keeping multiple copies of the objects or erasure to get a kind of generalized RAID5 capability. The replicated pools require more raw storage but implement all Ceph operations. The erasure-coded pools require less raw storage but only implement a subset of the available operations.

Type

String

Required

No

Default

replicated

crush-ruleset-name

Description

The name of the crush ruleset for the pool. If specified ruleset does not exist, the creation of the replicated pool fails with the ENOENT error. But the replicated pool will create a new erasure ruleset with the specified name.

Type

String

Required

No

Default

erasure-code for the erasure-coded pool. For the replicated pool, the value of the osd_pool_default_crush_replicated_ruleset variable is used from the Ceph configuration file.

expected-num-objects

Description

The expected number of objects for the pool. By setting this value together with a negative filestore merge threshold variable, the placement group directory is split at the pool creation time to avoid the latency impact to do a runtime directory splitting.

Type

Integer

Required

No

Default

0, no splitting at the pool creation time

erasure-code-profile

Description

For erasure-coded pools only. Use the erasure code profile. It must be an existing profile as defined by the osd erasure-code-profile set variable in the Ceph configuration file. For further information, see the Erasure Code Profiles section.

Type

String

Required

No

When you create a pool, set the number of placement groups to a reasonable value (for example to 100). Consider the total number of placement groups per OSD too. Placement groups are computationally expensive, so performance will degrade when you have many pools with many placement groups, for example, 50 pools with 100 placement groups each. The point of diminishing returns depends upon the power of the OSD host.

In-flight write operations may overrun pool quotas for a short time until Ceph propagates the pool usage across the cluster. This is normal behavior. Enforcing pool quotas on in-flight write operations would impose significant performance penalties.

4.5. Delete a Pool

If you created your own rulesets and rules for a pool you created, you should consider removing them when you no longer need your pool. If you created users with permissions strictly for a pool that no longer exists, you should consider deleting those users too.

4.6. Rename a Pool

To rename a pool, execute:

ceph osd pool rename <current-pool-name> <new-pool-name>

If you rename a pool and you have per-pool capabilities for an authenticated user, you must update the user’s capabilities (i.e., caps) with the new pool name.

4.7. Show Pool Statistics

To show a pool’s utilization statistics, execute:

rados df

4.8. Make a Snapshot of a Pool

To make a snapshot of a pool, execute:

ceph osd pool mksnap <pool-name> <snap-name>

Warning

If you create a pool snapshot, you will never be able to take RBD image snapshots within the pool and it will be irreversible.

4.11. Get Pool Values

4.12. Set the Number of Object Replicas

To set the number of object replicas on a replicated pool, execute the following command:

ceph osd pool set <poolname> size <num-replicas>

Important

The <num-replicas> parameter includes the object itself. If you want to include the object and two copies of the object for a total of three instances of the object, specify 3.

For example:

ceph osd pool set data size 3

You can execute this command for each pool.

Note

An object might accept I/O operations in degraded mode with fewer replicas than specified by the pool size setting. To set a minimum number of required replicas for I/O, use the min_size setting. For example:

ceph osd pool set data min_size 2

This ensures that no object in the data pool will receive I/O with fewer replicas than specified by the min_size setting.

4.13. Get the Number of Object Replicas

To get the number of object replicas, execute the following command:

ceph osd dump | grep 'replicated size'

Ceph will list the pools, with the replicated size attribute highlighted. By default, Ceph creates two replicas of an object, that is a total of three copies, or a size of 3.

4.14. Pool Values

Specifies the number of replicas for objects in the pool. See the Set the Number of Object Replicas section for further details. Applicable for the replicated pools only.

Type

Integer

min_size

Description

Specifies the minimum number of replicas required for I/O. See the Set the Number of Object Replicas section for further details. Applicable for the replicated pools only.

Type

Integer

pg_num

Description

The effective number of placement groups to use when calculating data placement.

Type

Integer

Valid Range

Superior to pg_num current value.

pgp_num

Description

The effective number of placement groups to use when calculating data placement.

Type

Integer

Valid Range

Equal to or less than what specified by the pg_num variable.

crush_ruleset

Description

The ruleset to use for mapping object placement in the cluster.

Type

Integer

hashpspool

Description

Enable or disable the HASHPSPOOL flag on a given pool. With this option enabled, pool hashing and placement group mapping are changed to improve the way pools and placement groups overlap.

Type

Integer

Valid Range

1 enables the flag, 0 disables the flag.

Important

Do not enable this option on production pools of a cluster with a large amount of OSDs and data. All placement groups in the pool would have to be remapped causing too much data movement.

nodelete

Description

Set/Unset NODELETE flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

nopgchange

Description

Set/Unset NOPGCHANGE flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

nosizechange

Description

Set/Unset NOSIZECHANGE flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

write_fadvise_dontneed

Description

Set/Unset WRITE_FADVISE_DONTNEED flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

noscrub

Description

Set/Unset NOSCRUB flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

nodeep_scrub

Description

Set/Unset NODEEP_SCRUB flag on a given pool.

Type

Integer

Valid Range

1 sets flag, 0 unsets flag.

hit_set_type

Description

Enables hit set tracking for cache pools.

Type

String

Valid Settings

bloom, explicit_hash, explicit_object

Default

bloom. Other values are for testing.

hit_set_count

Description

The number of hit sets to store for cache pools. The higher the number, the more RAM consumed by the ceph-osd daemon.

Type

Integer

Valid Range

1. Agent doesn’t handle > 1 yet.

hit_set_period

Description

The duration of a hit set period in seconds for cache pools. The higher the number, the more RAM consumed by the ceph-osd daemon.

Type

Integer

Example

3600 1hr

hit_set_fpp

Description

The false positive probability for the bloom hit set type.

Type

Double

Valid Range

0.0 - 1.0

Default

0.05

cache_target_dirty_ratio

Description

The percentage of the cache pool containing modified (dirty) objects before the cache tiering agent will flush them to the backing storage pool.

Type

Double

Default

.4

cache_target_dirty_high_ratio

Description

The percentage of the cache pool containing modified (dirty) objects before the cache tiering agent will flush them to the backing storage pool with a higher speed.

Type

Double

Default

.6

cache_target_full_ratio

Description

The percentage of the cache pool containing unmodified (clean) objects before the cache tiering agent will evict them from the cache pool.

Type

Double

Default

.8

target_max_bytes

Description

Ceph will begin flushing or evicting objects when the max_bytes threshold is triggered.

Type

Integer

Example

1000000000000 #1-TB

target_max_objects

Description

Ceph will begin flushing or evicting objects when the max_objects threshold is triggered.

Type

Integer

Example

1000000 #1M objects

hit_set_grade_decay_rate

Description

Temperature decay rate between two successive hit_sets.

Type

Integer

Valid Range

0 - 100

Default

20

hit_set_search_last_n

Description

Count at most N appearance in hit_sets for temperature calculation.

Type

Integer

Valid Range

0 - hit_set_count

Default

1

cache_min_flush_age

Description

The time (in seconds) before the cache tiering agent will flush an object from the cache pool to the storage pool.

Type

Integer

Example

600 10min

cache_min_evict_age

Description

The time (in seconds) before the cache tiering agent will evict an object from the cache pool.

Type

Integer

Example

1800 30min

fast_read

Description

On a pool that uses erasure coding, if this flag is enabled, the read request issues subsequent reads to all shards, and wait until it receives enough shards to decode to serve the client. In the case of the jerasure and isa erasure plug-ins, once the first K replies return, client’s request is served immediately using the data decoded from these replies. This helps to allocate some resources for better performance. Currently this flag is only supported for erasure coding pools.

Type

Boolean

Defaults

0

scrub_min_interval

Description

The minimum interval in seconds for pool scrubbing when load is low. If it is 0, Ceph uses the osd_scrub_min_interval setting from the Ceph configuration.

Type

Double

Default

0

scrub_max_interval

Description

The maximum interval in seconds for pool scrubbing irrespective of cluster load. If it is 0, Ceph uses the osd_scrub_max_interval setting from the Ceph configuration.

Type

Double

Default

0

deep_scrub_interval

Description

The interval in seconds for pool “deep” scrubbing. If it is 0, Ceph uses the osd_deep_scrub_interval setting from the Ceph configuration.

Type

Double

Default

0

Chapter 5. Erasure Code Pools

Ceph storage strategies involve defining data durability requirements. Data durability means the ability to sustain the loss of one or more OSDs without losing data.

Ceph stores data in pools and there are two types of the pools:

replicated

erasure-coded

Ceph uses the replicated pools by default, meaning the Ceph copies every object from a primary OSD node to one or more secondary OSDs.

The erasure-coded pools reduces the amount of disk space required to ensure data durability but it is computationally a bit more expensive than replication.

Erasure coding is a method of storing an object in the Ceph storage cluster durably where the erasure code algorithm breaks the object into data chunks (k) and coding chunks (m), and stores those chunks in different OSDs.

In the event of the failure of an OSD, Ceph retrieves the remaining data (k) and coding (m) chunks from the other OSDs and the erasure code algorithm restores the object from those chunks.

Erasure coding uses storage capacity more efficiently than replication. The n-replication approach maintains n copies of an object (3x by default in Ceph), whereas erasure coding maintains only k + m chunks. For example, 3 data and 2 coding chunks use 1.5x the storage space of the original object.

While erasure coding uses less storage overhead than replication, the erasure code algorithm uses more RAM and CPU than replication when it accesses or recovers objects. Erasure coding is advantageous when data storage must be durable and fault tolerant, but do not require fast read performance (for example, cold storage, historical records, and so on).

Ceph creates a default erasure code profile when initializing a cluster with k=2 and m=1, This mean that Ceph will spread the object data over three OSDs (k+m == 3) and Ceph can lose one of those OSDs without losing data. To know more about erasure code profiling see the Erasure Code Profiles section.

Note

Erasure-coded pools are only supported with the Ceph Object Gateway. Using erasure-coded pools with a Ceph Block Device is not supported.

Important

Configure only the .rgw.buckets pool as erasure-coded and all other Ceph Object Gateway pools as replicated, otherwise an attempt to create a new bucket fails with the following error:

set_req_state_err err_no=95 resorting to 500

The reason for this is that erasure-coded pools do not support the omap operations and certain Ceph Object Gateway metadata pools require the omap support.

5.1. Creating a Sample Erasure-coded Pool

The simplest erasure coded pool is equivalent to RAID5 and requires at least three hosts:

5.2. Erasure Code Profiles

Ceph defines an erasure-coded pool with a profile. Ceph uses a profile when creating an erasure-coded pool and the associated CRUSH ruleset.

Ceph creates a default erasure code profile when initializing a cluster and it provides the same level of redundancy as two copies in a replicated pool. However, it uses 25% less storage capacity. The default profiles defines k=2 and m=1, meaning Ceph will spread the object data over three OSDs (k+m=3) and Ceph can lose one of those OSDs without losing data.

The default erasure code profile can sustain the loss of a single OSD. It is equivalent to a replicated pool with a size two, but requires 1.5 TB instead of 2 TB to store 1 TB of data. To display the default profile use the following command:

You can create a new profile to improve redundancy without increasing raw storage requirements. For instance, a profile with k=8 and m=4 can sustain the loss of four (m=4) OSDs by distributing an object on 12 (k+m=12) OSDs. Ceph divides the object into 8 chunks and computes 4 coding chunks for recovery. For example, if the object size is 8 MB, each data chunk is 1 MB and each coding chunk has the same size as the data chunk, that is also 1 MB. The object will not be lost even if four OSDs fail simultaneously.

The most important parameters of the profile are k, m and ruleset-failure-domain, because they define the storage overhead and the data durability.

Important

Choosing the correct profile is important because you cannot change the profile after you create the pool. To modify a profile, you must create a new pool with a different profile and migrate the objects from the old pool to the new pool.

For instance, if the desired architecture must sustain the loss of two racks with a storage overhead of 40% overhead, the following profile can be defined:

The primary OSD will divide the NYAN object into four (k=4) data chunks and create two additional chunks (m=2). The value of m defines how many OSDs can be lost simultaneously without losing any data. The ruleset-failure-domain=rack will create a CRUSH ruleset that ensures no two chunks are stored in the same rack.

Important

Red Hat supports the following jerasure coding values for k, and m:

k=8 m=3

k=8 m=4

k=4 m=2

Important

If the number of OSDs lost equals the number of coding chunks (m), some placement groups in the erasure coding pool will go into incomplete state. If the number of OSDs lost is less than m, no placement groups will go into incomplete state. In either situation, no data loss will occur. If placement groups are in incomplete state, temporarily reducing min_size of an erasure coded pool will allow recovery.

Each object is split in data-chunks parts, each stored on a different OSD.

Type

Integer

Required

Yes.

Example

4

m

Description

Compute coding chunks for each object and store them on different OSDs. The number of coding chunks is also the number of OSDs that can be down without losing data.

Type

Integer

Required

Yes.

Example

2

technique

Description

The more flexible technique is reed_sol_van; it is enough to set k and m. The cauchy_good technique can be faster but you need to chose the packetsize carefully. All of reed_sol_r6_op, liberation, blaum_roth, liber8tion are RAID6 equivalents in the sense that they can only be configured with m=2.

The encoding will be done on packets of bytes size at a time. Choosing the correct packet size is difficult. The jerasure documentation contains extensive information on this topic.

Type

Integer

Required

No.

Default

2048

ruleset-root

Description

The name of the CRUSH bucket used for the first step of the ruleset. For instance step take default.

Type

String

Required

No.

Default

default

ruleset-failure-domain

Description

Ensure that no two chunks are in a bucket with the same failure domain. For instance, if the failure domain is host no two chunks will be stored on the same host. It is used to create a ruleset step such as step chooseleaf host.

Type

String

Required

No.

Default

host

directory

Description

Set the directory name from which the erasure code plug-in is loaded.

Type

String

Required

No.

Default

/usr/lib/ceph/erasure-code

--force

Description

Override an existing profile by the same name.

Type

String

Required

No.

5.3.2. Locally Repairable Erasure Code (LRC) Plugin

With the jerasure plug-in, when Ceph stores an erasure-coded object on multiple OSDs, recovering from the loss of one OSD requires reading from all the others. For instance if you configure jerasure with k=8 and m=4, losing one OSD requires reading from the eleven others to repair.

The lrc erasure code plug-in creates local parity chunks to be able to recover using fewer OSDs. For instance if you configure lrc with k=8, m=4 and l=4, it will create an additional parity chunk for every four OSDs. When Ceph loses a single OSD, it can recover the object data with only four OSDs instead of eleven.

Although it is probably not an interesting use case when all hosts are connected to the same switch, you can actually observe reduced bandwidth usage between racks when using the lrc erasure code plug-in.

Each object is split in data-chunks parts, each stored on a different OSD.

Type

Integer

Required

Yes.

Example

4

m

Description

Compute coding chunks for each object and store them on different OSDs. The number of coding chunks is also the number of OSDs that can be down without losing data.

Type

Integer

Required

Yes.

Example

2

l

Description

Group the coding and data chunks into sets of size locality. For instance, for k=4 and m=2, when locality=3 two groups of three are created. Each set can be recovered without reading chunks from another set.

Type

Integer

Required

Yes.

Example

3

ruleset-root

Description

The name of the crush bucket used for the first step of the ruleset. For instance step take default.

Type

String

Required

No.

Default

default

ruleset-locality

Description

The type of the crush bucket in which each set of chunks defined by l will be stored. For instance, if it is set to rack, each group of l chunks will be placed in a different rack. It is used to create a ruleset step such as step choose rack. If it is not set, no such grouping is done.

Type

String

Required

No.

ruleset-failure-domain

Description

Ensure that no two chunks are in a bucket with the same failure domain. For instance, if the failure domain is host no two chunks will be stored on the same host. It is used to create a ruleset step such as step chooseleaf host.

Type

String

Required

No.

Default

host

directory

Description

Set the directory name from which the erasure code plug-in is loaded.

Type

String

Required

No.

Default

/usr/lib/ceph/erasure-code

--force

Description

Override an existing profile by the same name.

Type

String

Required

No.

5.3.2.2. Create a Low-level LRC Profile

The sum of k and m must be a multiple of the l parameter. The low level configuration parameters do not impose such a restriction and it may be more convenient to use it for specific purposes. It is for instance possible to define two groups, one with 4 chunks and another with 3 chunks. It is also possible to recursively define locality sets, for instance data centers and racks into data centers. The k/m/l are implemented by generating a low level configuration.

The lrc erasure code plug-in recursively applies erasure code techniques so that recovering from the loss of some chunks only requires a subset of the available chunks, most of the time.

For instance, when three coding steps are described as:

chunk nr 01234567
step 1 _cDD_cDD
step 2 cDDD____
step 3 ____cDDD

where c are coding chunks calculated from the data chunks D, the loss of chunk 7 can be recovered with the last four chunks. And the loss of chun 2 chunk can be recovered with the first four chunks.

The miminal testing scenario is strictly equivalent to using the default erasure-code profile. The DD implies K=2, the c implies M=1 and uses the jerasure plug-in by default.

The lrc plug-in is particularly useful for reducing inter-rack bandwidth usage. Although it is probably not an interesting use case when all hosts are connected to the same switch, reduced bandwidth usage can actually be observed. It is equivalent to k=4, m=2 and l=3 although the layout of the chunks is different:

LRC now uses jerasure as the default EC backend. It is possible to specify the EC backend and algorithm on a per layer basis using the low level configuration. The second argument in layers='[ [ "DDc", "" ] ]' is actually an erasure code profile to be used for this level. The example below specifies the ISA backend with the Cauchy technique to be used in the lrcpool.:

5.3.3. Controlling CRUSH Placement

The default CRUSH ruleset provides OSDs that are on different hosts. For instance:

chunk nr 01234567
step 1 _cDD_cDD
step 2 cDDD____
step 3 ____cDDD

needs exactly 8 OSDs, one for each chunk. If the hosts are in two adjacent racks, the first four chunks can be placed in the first rack and the last four in the second rack. Recovering from the loss of a single OSD does not require using bandwidth between the two racks.

Each object is split in data-chunks parts, each stored on a different OSD.

Type

Integer

Required

No.

Default

7

m

Description

Compute coding chunks for each object and store them on different OSDs. The number of coding chunks is also the number of OSDs that can be down without losing data.

Type

Integer

Required

No.

Default

3

technique

Description

The ISA plug-in comes in two Reed Solomon forms. If reed_sol_van is set, it is Vandermonde, if cauchy is set, it is Cauchy.

Type

String

Required

No.

Valid Settings

reed_sol_vancauchy

Default

reed_sol_van

ruleset-root

Description

The name of the crush bucket used for the first step of the ruleset. For intance step take default.

Type

String

Required

No.

Default

default

ruleset-failure-domain

Description

Ensure that no two chunks are in a bucket with the same failure domain. For instance, if the failure domain is host no two chunks will be stored on the same host. It is used to create a ruleset step such as step chooseleaf host.

Type

String

Required

No.

Default

host

directory

Description

Set the directory name from which the erasure code plug-in is loaded.

Type

String

Required

No.

Default

/usr/lib/ceph/erasure-code

--force

Description

Override an existing profile by the same name.

Type

String

Required

No.

5.5. Pyramid Erasure Code

Pyramid erasure code is basically an improved algorithm based on the original erasure code algorithm to improve the access and recovery of data. It is simply a derivation of any existing MDS (Maximum Distance Separable) code like Reed-Solomon for any given (n, k) where k is the original number of data chunks and n is the total number of data chunks after the coding process. As Pyramid code is based on standard MDS code, it has the same encoding/decoding approach. A pyramid coded data pool has the same write overhead and same recovery ability of arbitrary failures like a normal erasure coded pool. The only advantage of pyramid code is that it significantly reduces the read overhead in comparison to normal erasure code.

Let’s take an example of a (11, 8) erasure coded pool and apply the pyramid code approach on it. We will convert the (11, 8) erasure coded pool into a (12, 8) Pyramid coded pool. The erasure coded pool has 8 data chunks and 11 - 8 = 3 redundant chunks. The Pyramid Code separates the 8 data chunks into 2 equal size groups, say P1 = {a1, a2, a3, a4} and P2 = {a5, a6, a7, a8}. It keeps two of the redundant chunks from the erasure code unchanged (say b2 and b3). These two chunks are now called global redundant chunks, because they cover all the 8 data chunks. Next, a new redundant chunk is computed for group P1, which is denoted as group (or local) redundant chunk b1,1. The computation is done as if computing b1 in the original erasure code, except for setting all the data chunks in P2 to 0. Similarly, a group redundant chunks b1,2 is computed for P2. The group redundant chunks are only affected by data chunks in the corresponding groups and not by other groups at all. The group redundant chunks can be interpreted as the projection of the original redundant chunk in the erasure code onto each group i.e, b1,1 + b1,2 = b1. So, in this approach, when one data chunk fails, it can be recovered using a read overhead of 4 instead of 8 for the normal erasure coded pool. For instance, if a3 in P1 fails and a1 is the primary OSD in charge of scrubbing, it can use a1, a2, a4 and b1,1 to recover a3 instead of reading from P2. Reading all chunks is only required when more than one chunk goes missing in the same group.

This Pyramid code has the same write overhead as the original erasure code. Whenever any data chunk is updated, the Pyramid Code needs to update 3 redundant chunks (both b2, b3, plus either b1,1 or b1,2), while the erasure code also updates 3 redundant chunks (b1, b2 and b3). Also, it can recover 3 arbitrary erasures same as the normal erasure code. The only benefit is lesser read overhead as mentioned above which comes at the cost of using one additional redundant chunk. So, Pyramid code trades storage space for access efficiency.

The below diagram shows the constructed pyramid code:

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